A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. In recent years, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management and so on. Techniques for building Chinese knowledge graphs are also developing rapidly and different Chinese knowledge graphs have been constructed to support various applications. Under the background of the “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China in developing knowledge graphs is also a good reference to develop non-English knowledge graphs. In this paper, we aim to introduce the techniques of constructing Chinese knowledge graphs and their applications, as well as analyse the impact of knowledge graph on OBOR. We first describe the background of OBOR, and then introduce the concept and development history of knowledge graph and typical Chinese knowledge graphs. Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs. Finally, we list some examples to explain the potential impacts of knowledge graph on OBOR.

[1]  Juan-Zi Li,et al.  Cross-lingual knowledge linking across wiki knowledge bases , 2012, WWW.

[2]  Dongyan Zhao,et al.  A Chinese Question Answering System for Single-Relation Factoid Questions , 2017, NLPCC.

[3]  Peter F. Patel-Schneider,et al.  "Reducing" CLASSIC to Practice: Knowledge Representation Theory Meets Reality , 1999, Artif. Intell..

[4]  Haofen Wang,et al.  An effective rule miner for instance matching in a web of data , 2012, CIKM.

[5]  Hao Wang,et al.  A Hybrid Method for Chinese Entity Relation Extraction , 2014, NLPCC.

[6]  Seung-won Hwang,et al.  Cross-Lingual Type Inference , 2016, DASFAA.

[7]  Wei Zhang,et al.  Knowledge vault: a web-scale approach to probabilistic knowledge fusion , 2014, KDD.

[8]  Peng Zhang,et al.  XLore: A Large-scale English-Chinese Bilingual Knowledge Graph , 2013, SEMWEB.

[9]  Jeff Z. Pan,et al.  Effective Online Knowledge Graph Fusion , 2015, International Semantic Web Conference.

[10]  Oren Etzioni,et al.  Chinese Open Relation Extraction for Knowledge Acquisition , 2014, EACL.

[11]  Yanghua Xiao,et al.  How to Keep a Knowledge Base Synchronized with Its Encyclopedia Source , 2017, IJCAI.

[12]  Aditya Kalyanpur,et al.  Leveraging Community-Built Knowledge for Type Coercion in Question Answering , 2011, International Semantic Web Conference.

[13]  Seung-won Hwang,et al.  KBQA: Learning Question Answering over QA Corpora and Knowledge Bases , 2019, Proc. VLDB Endow..

[14]  Guilin Qi,et al.  Mining Type Information from Chinese Online Encyclopedias , 2014, JIST.

[15]  Wentao Ding,et al.  An EBMC-Based Approach to Selecting Types for Entity Filtering , 2015, AAAI.

[16]  Jiangang Zhu,et al.  On building and publishing Linked Open Schema from social Web sites , 2018, J. Web Semant..

[17]  Yongbin Liu,et al.  Building a Large-Scale Cross-Lingual Knowledge Base from Heterogeneous Online Wikis , 2015, NLPCC.

[18]  Guilin Qi,et al.  Zhishi.schema Explorer: A Platform for Exploring Chinese Linked Open Schema , 2014, CSWS.

[19]  John F. Sowa,et al.  Principles of semantic networks , 1991 .

[20]  Lenhart K. Schubert Extending The Expressive Power Of Semantic Networks , 1976, IJCAI.

[21]  Bin Liang,et al.  CN-DBpedia: A Never-Ending Chinese Knowledge Extraction System , 2017, IEA/AIE.

[22]  Jens Lehmann,et al.  DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia , 2015, Semantic Web.

[23]  Yue Zhang,et al.  ZORE: A Syntax-based System for Chinese Open Relation Extraction , 2014, EMNLP.

[24]  Karl Aberer,et al.  TRank: Ranking Entity Types Using the Web of Data , 2013, International Semantic Web Conference.

[25]  Bertram C. Bruce,et al.  Some Relations Between Predicate Calculus and Semantic Net Representations of Discourse , 1971, IJCAI.

[26]  Guilin Qi,et al.  Zhishi.me - Weaving Chinese Linking Open Data , 2011, SEMWEB.

[27]  Fabian M. Suchanek,et al.  YAGO3: A Knowledge Base from Multilingual Wikipedias , 2015, CIDR.

[28]  Ian Horrocks The FaCT System , 1998, TABLEAUX.

[29]  Bin Luo,et al.  Language-Independent Type Inference of the Instances from Multilingual Wikipedia , 2019, Int. J. Semantic Web Inf. Syst..

[30]  Guilin Qi,et al.  On Publishing Chinese Linked Open Schema , 2014, International Semantic Web Conference.

[31]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[32]  Juan-Zi Li,et al.  Boosting Cross-Lingual Knowledge Linking via Concept Annotation , 2013, IJCAI.

[33]  David S. Touretzky,et al.  Cancellation in a Parallel Semantic Network , 1981, IJCAI.